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Linking Entrepreneurship and Total Factor Productivity What are the Economic

Setting Required?

Doaa M. Salman and Karim Badr

Paper prepared for the 17th annual international conference of the ERF Page 1

Linking Entrepreneurship and total factor productivity What are the economic setting required? Doaa M. Salman, Karim Badr, MSA University, Egypt World Bank, Egypt Email: [email protected]. Email: [email protected]

Abstract: This paper attempts to fill this gap by highlighting the linkage between entrepreneur, total factor productivity and growths. This paper addresses the correlation between innovative entrepreneurs and total factor productivity growth. Moreover, this research aims at determining the economic settings and institutions that are correlated with higher impact of entrepreneurship on productivity. Results showed that total factor productivity is significant and positively correlated with entrepreneurship; albeit somewhat lower when OLS estimation techniques are used, suggesting that there is a positive relationship between research and development, tertiary school enrolment, imports and inflation. Moreover, it is negatively correlated with imports. Entrepreneurship is one instrument that may add to the effect of knowledge investments through R&D. This is certainly consistent with the recent statistical, systematic empirical evidence linking measures of entrepreneurship to economic growth. Implementing different regression techniques we find surprisingly robust support for entrepreneurship being one important source of growth. Key words: Total Factor Productivity, Entrepreneur, ICT, Growth.


1. Introduction

Since Solow’s (1957) measurement of technical change over time, using macro data in the United States, the significance of examining total factor productivity, defined as output per unit of total input, came to be recognized. Empirical studies on economic growth, after accounting for physical and human capital accumulation 'something else' generates growth in most countries. Research on growth accounting finds out that most of the differences come from the cross-country differences in total factor productivity (Klenow and Rodriguez-Clare, 1997; Hall and Jones, 1999). The role of total factor productivity (TFP) growth has been much discussed in endogenous growth theory because it’s evidently contributes to endogenous growth, Solow (2000). Researchers investigated for the link of enhancing human capital accumulation and economic growth. Carree et. al, (2002), have reported negative correlation between economic development and business ownership. As the country enjoys higher level of per capita income, and consequently higher wages, the opportunity cost of switching from employee to business owner increases. On the contrary, more recent studies have showed different results. The rate of business ownership has been rising over the 1990s and onwards. One reason is the emergence of new industries such as ICT, software, and biotechnology. TFP refers to additional output stimulated by enhancements in efficiency that are accounted for by such factors as advancement in human capital, skills and expertise, acquisition of efficient institutional techniques, economic variable, innovation or upgrading of technology, and enhancement in Information communication technology ICT. The role of ICT in growth theories is viewed as a factor input that contributes to economic growth through TFP and capital deepening. The process becomes more complicated, however, when one must account for the role of knowledge in that growth. Knowledge mostly recognized with pure technological progress, so that it is directly linked to R&D investment. Audretsch and Thurik (2002) explained that globalization and the information revolution shifted away the comparative advantages of firms in traditional industries. However, if technical change spurs smart growth, while capital and labor are sources of growth by brutal force (Baumol 2007), one shall inquire about the role of entrepreneurs (as a vehicle for innovation) in explaining and enhancing total factor productivity, in the context of developing countries, and Egypt. As simple as it may appear, the causes rooted in entrepreneur issue that have not been stressed in an adequate manner. This research attempts to fill this gap by highlighting the linkage between entrepreneur, total factor productivity and growths. This paper addresses the correlation between innovative entrepreneurs and total factor productivity. Moreover, this research aims at determining the economic settings and institutions that are correlated with higher impact of entrepreneurship on productivity. The structure of the paper is as follows. Section 2 presents the link between Entrepreneurship and total factor productivity from an empirical perspective. Section 3 describes the model, data and variables used in this study. Section 4 presents the empirical results of our analyses and Section 5 concludes.


2. Linking Entrepreneurship and total factor productivity

The present section attempts to link the important role of entrepreneurship with total factor productivity level.

2.1 Entrepreneurship and Economic Growth The relationship between entrepreneurship and economic growth is elusive or at best indirect, one reason might be the difficulty associated with measuring entrepreneurship. Several proxies are being used to measure entrepreneurship as business ownership rate, entry rate, self employment rate, none of them is a synonym to entrepreneurship, as business owners might not venture in entrepreneurial innovative activities, and also entrepreneurs might not be business owners (Intrapreneurs). Entrepreneurs, especially innovative ones, are linchpin to the process of development (Schumpeter 1912). However, scholars admitted these proxies to be acceptable measurement to entrepreneurship (Van Stel & Carree, 2002). Furthermore, some authors have reported negative correlation between economic development and business ownership. As the country enjoys higher level of per capita income, and consequently higher wages, the opportunity cost of switching from employee to business owner increases. (Carree et. al, 2002) However, “as economic growth is concerned, innovative entrepreneur is what matters most” (Baumol 2007). There are several classifications to entrepreneurs; among them is the distinction between innovative and “replicative” entrepreneurs. The latter are important in poverty alleviation, employment creation, welfare (Tamvada, 2009), and income inequality Kimhi (2009). On the other hand, more recent studies have showed different results. The rate of business ownership has been rising over the 1990s and onwards. One reason is the emergence of new industries such as ICT, software, and biotechnology. Audretsch and Thurik (2002) explained that globalization and the information revolution shifted away the comparative advantages of firms in traditional industries. Furthermore, globalization and fierce competition forced large firm to focus on their comparative advantage and to outsource all other secondary lines of business. The Global Entrepreneurship Monitor 2000 concludes that there is a strong relationship between entrepreneurial activities, defined as start-up activities, and economic growth. Scholars emphasize two roles of entrepreneurs that drive growth, competition (measured by new entry) and innovation (Thurik & Wennekers, 1999). Carree, et, al. (2002) addressed the issue of business ownership rate optimality. They showed that any deviation from the equilibrium (optimal) rate of business ownership shall penalize the growth rate of any economy in the medium term. A shortage in business ownership shall result in decreasing competition, decreasing efficiency and shall harm innovation. On the other hand, excessive business ownership rate shall cause firms to operate at diseconomies of scale and “will result in a large number of entrepreneurs absorbing capital and energy that could have been allocated more productively elsewhere”. Van Stel and Carree conclude that the relationship between business ownership and economic development is U-shaped. They showed that sectoral business ownership is a function of economic development, expected to have negative relationship with developing countries at the early stages of industrialization where these countries invest heavily in production, distribution, and management to benefit from economies of scale. While at higher levels of economic development, the relationship is expected to be positive since developed countries have witnessed a shift away from traditional industries towards software, electronics, ICT, and biotechnology, where small firms can significantly participate, hence; a higher rate of business ownership (Van Stel and Carree 2002).


Measuring entrepreneurship at the level of a country is a complex task due to its multidimensional nature, as evidenced by the progress of the domain (Gartner and Shane, 1995; Van Stel, Carree, and Thurik, 2005). At the country level, entrepreneurship measures often employ the number of self-employed individuals or business start-ups or the prevalence of small businesses as a proxy for entrepreneurial activity. In this paper we use the cost of start up business and number of trademarks registered which are some variables correlated with innovative entrepreneur. It is likely the case that some of the variation relates to different definitions of entrepreneurship. Further, even if the measures—are accurate and are not derived from self-reports, they are not fully comparable across countries due to differences in the definition of entry rates (Hoffmann, Larsen, and Oxholm, 2006). Despite these challenges, the differences are usually attributed to variations in the institutional factors influencing entrepreneurial activity. Global Entrepreneurship Monitor (GEM) study shows that the less developed countries outrun their innovation-driven counterpart in the Total entrepreneurship activity rate this variance is due to the differences in the type of entrepreneurial activities in these countries; that vary between replicative and motivate one. This has been highlighted by Acs and Varga (2005) and several others, who found that opportunity-driven entrepreneur ship has a positive effect on economic development. Eurostat proposed a set of proxies for entrepreneurship or entrepreneurs (OECD/Eurostat, 2008).

Figure one

2.2 Entrepreneurship and total factor productivity

Erken, et. al. used Compendia dataset to assess the role of entrepreneurship in total factor productivity. They re-estimated the models on the drivers of productivity presented in five papers (Coe and Helpman, 1995; Engelbrecht, 1997; Griffith et al., 2004; Guellec and Van Pottelsberghe de la Potterie, 2004; Belorgey et al., 2006) and incorporating entrepreneurship to these models. The data included 20 OECD countries for 32 year period (1971-2002). Entrepreneurship was measured as the ratio between actual and equilibrium business ownership rates. Their findings confirmed the results of the five seminal studies as public and private research and development, human capital, technology, and other variables are significant drivers of TFP. In addition, they showed that entrepreneurship has a significant impact on TFP (Erken, Donselaar, & Thurik, 2008). Thus, the absence of a clear long-run relationship between entrepreneurship and economic growth and/or productivity makes the suspected importance of entrepreneurship between academic researchers. Solow (1957) showed that total factor productivity is accountable to 88.5% of growth in United States, and other factors of production (capital and labor) only contribute 12.5%. Kheir El Din and Morsi showed that total factor productivity growth drove economic growth in Egypt from


1991 to 1998, replacing the role played by capital, although they explicated this shift by deficiency in capital accumulation rather than amelioration in TFP. However, if technical change spurs smart growth, while capital and labor are sources of growth by brutal force (Baumol 2007), one shall inquire about the role of entrepreneurs (as a vehicle for innovation) in explaining and enhancing total factor productivity, in the context of developing countries. Meanwhile, in the field of entrepreneurship study, since Lucas (1978) a considerable number of papers have used a production function approach that explicitly includes variables for entrepreneurial ability” in the model for the TFP and the assumption of decreasing returns to scale (e.g., Evans and Jovanovic, 1989; Holtz-Eakin, Joulfaian and Rosen, 1994; Dunn and Holtz-Eakin, 2000; Gentry and Hubbard, 2000b). The relation between total factor productivity and R&D empirically using the R&D capital approach in literature has been examined by many researchers (Coe and Helpman, 1995; Guellec and Van Pottelsberghe de la Potterie, 2004; Griliches and Lichtenberg, 1984). These studies generally find strong results concerning the contribution of R&D capital to TFP growth. They illustrated that the impact of domestic R&D capital is dependent on the economic size of countries. Larger economies benefit more than smaller ones from domestic R&D capital as they consist of a larger share of worldwide R&D; the flow of R& D to foreign countries will be absorbed principally within the home country and finally because they perform R&D across a wide array of possible R&D activities. While the role of ICT in growth theories is viewed as a factor input that contributes to economic growth through TFP and capital deepening. ICT may have a positive impact on economic growth if appropriate policies are adopted to promote its development. This argument rests on the hypothesis that market forces, together with sounding government policies, may prove sufficient to generate economic development. Thus, policies adopted knowledge based economies to promotes employment and skills, this is based upon the estimates that by 2010 half of all jobs will be in industries that are major producers or intensive users of e-commerce industries, and wider technology, media information technology products and services The policy suggestions explicitly link these developments to the encouragement of entrepreneurship in new services and businesses, particularly through fiscal policies rewarding risk taking (such as stock options), and with a strong territorial dimension (CEC, 1999a). Scholars demonstrate that institutional structure such as; culture, legal environment, economic incentives, and traditions influence the development of industries and the success of entrepreneurial firms within industries (Aldrich and Fiol, 1994; Baumol, Litan, and Schramm, 2007). Thus it is institutional structure that promotes productive, wealth-generating entrepreneurial activity which is the source of economic growth. The use of entrepreneurship measures to explain productivity is linked by the role of economic development. The negative relationship between business ownership and economic development is examined (Kuznets, 1971; Schultz, 1990; Yamada, 1996). The growing importance of economies of scale is mentioned as the explanation (Chandler, 1990: Teece, 1993). The reversal of this trend is first observed by Blau (1987) and Acs, Audretsch and Evans (1994) and attributed to technological changes leading to a reduction of the role of economies of scale.


2.3 Sounding economic setting- General Frame Work The following section suggests a general framework for achieving a sounding economic setting. This setting passed through the following stages. Stage one focuses upon the existing of innovate entrepreneurs, this stage represent the resource availability stage. Second, start up stage, concerns with the process of determinates of productivity growth. Third, take off; this stage is based on R&D and ICT as pillar for the dynamism of growth that can lead to development.

Figure 2 General frame work for the proposed sounding economic setting

Stage one: entry; Existing of an entrepreneur is regarded as someone who creates, organize and maybe operate a business firm. Entrepreneurs are those who adopt new combination of means of productions’, through venturing in new businesses, entrepreneurs contribute to total output and hence to growth. Within the new challenges that globalization creates changes in ICT have opened new arenas that required continuous update to the relation between organization and people- certainly the ‘Schumpeterian revolution’. More generally, a mix between innovation and opportunity seeking, that required endogenous; technological capability and market opportunity dynamism which lead to the second stage. Stage two: Start up; Existing of entrepreneurs with their capabilities are necessary but not sufficient to have a significant impact on economic growth, the issue that required sounding institutional setting. Thus, it is not surprising that institutional theory has proven to be a powerful theoretical foundation for investigating role of entrepreneurship scholars (Bruton et al., 2010). To ensure the role of institutional setting a wide and multiple country databases are required to assure the role that institutions play in the rate and type of entrepreneurial activity, and provide the ability for scholars to both test and extend theory. The existing paper highlights several potential determinants of institutional factors that affect productivity growth such as; inflation, trade openness, the level of education, and several institutional factors. In this paper we used only inflation and exports and imports are tested. Than Institutional settings “rules of the game” that would foster innovative entrepreneurial activities can be done through; Easiness of doing business, Institutions that shall reward innovative entrepreneurs; as patents and IPR, government role in fostering innovative an productive entrepreneurial activities and limiting destructive ones, the incentive structure for sustaining continuous innovation using subsidies and taxes, and linking R&D centers with Entrepreneurs through programs. Stage three: take-off; represent the role of entrepreneur influences knowledge and how knowledge thereby can be more or less easily turned into business activity and reflect on economic growth. In this part we tempted to assess the impact of stage one; entry rate and economic growth, we use cross sectional data, of 66 countries in different development levels, from the 2008 World Bank

Invovative

Entrepreneurship

Growth

Development


Group Entrepreneurship Survey that measure entrepreneurial activities in several countries, the correlation between entry rate and growth rate was tested. Results show a positive significant correlation between growth rate and entry rate, as entry rate increased by 1%, growth rate increased by 0.45% (see table 2). This finding is in conformity with the vast theoretical and empirical research the advocated the role of entrepreneurs, especially, establishing new business organizations, in promoting growth. However, the causality riddle still holds, does high entry rates cause growth rates to increase, or already developed countries enjoy high entrepreneurial activity and hence high entry rates. This dilemma is in the core of the relation between entrepreneurship and development. Carree, et, al. (2002) addressed the issue of business ownership rate optimality. They showed that any deviation from the equilibrium (optimal) rate of business ownership shall penalize the growth rate of any economy in the medium term. A shortage in business ownership shall result in decreasing competition, decreasing efficiency and shall harm innovation. On the other hand, excessive business ownership rate shall cause firms to operate at diseconomies of scale and “will result in a large number of entrepreneurs absorbing capital and energy that could have been allocated more productively elsewhere”. Van Stel and Carree (2004) criticized the previous paper for ignoring employment structure per sector. Since business ownership is higher in service sector compared to manufacturing, deviation from optimal rate may not be a problem of business ownership, but rather a problem of sectoral structure. They add that sectoral business ownership is a function of economic development, expected to have negative relationship with developing countries at the early stages of industrialization where these countries invest heavily in production, distribution, and management to benefit from economies of scale. While at higher levels of economic development, the relationship is expected to be positive since developed countries have witnessed a shift away from traditional industries towards software, electronics, ICT, and biotechnology, where small firms can significantly participate, hence; a higher rate of business ownership. Moreover, new technology has undermined the importance of economies of scale. Furthermore, high level of economic development entails high income levels which in turn widen the scope of individual demand; consequently creating opportunities for small ventures to appear. Stel and Carree conclude that the relationship between business ownership and economic development is U-shaped where business ownership decrease with low level of income, then increase as income increases. Stel and Caree showed an equilibrium (optimal ) level of business ownership and any deviation from this optimal shall harm growth, either because of diseconomies of scale, in case of too many entrepreneurship; or lack of competition and efficiency in case of shortage in entrepreneurs. We used the data from New Entrepreneurship International (GEM) for the year 2008 for 42 developed and developing countries to test this U-shaped function between entrepreneurship index and level of economic development. We used the total entrepreneurship index developed by Global Entrepreneurship Monitor (GEM) as a proxy for entrepreneurship, and the independent variables are log GDP per capita and log GDP per capita squared. Total Entrepreneurial Index = α + β1 Log GDP/Capita + β2 Log (GDP/Capita2) + ε

For the U-Shaped relationship, we expect B1 be negative and B2 to be positive, empirical results presented in table 1.A, present that, B1 has a negative sign, and B2 has a positive sign, and both are statistically significant. R2 is 38.6% and adjusted R2 is 35.5%. This empirical result confirms


with the hypothesis that the relationship between entrepreneurship and economic development is U-Shaped, as low income countries has low level of entrepreneurship and high income countries have high level of entrepreneurship. 3. Empirical analysis: The conceptual framework of this paper analyzes the underlying incentives and constraints faced by policy-makers in their strategic decisions regarding productivity. This paper tackles the research questions using simultaneous equations. Later, we grouped countries based on the Human Development Index (HDI) 3.1Varriables This paper starts by regress business entry on cost of starting business (% of GNI / Capita), time to start business, trade (% of GDP), and number of trademarks registered. Than predicting for the predict entrepreneurship (entrep). While, Step3: regress tfp (total factor productivity) on entrep, research and development exp. (% of GDP), territory school enrollment, imports (% of GDP), exports (% of GDP), and inflation. See table 2. 3.2 Econometric specification We used panel data set for 210 countries for nine consecutive years from 2000 to 2008. Total factor productivity was calculated by the researches as follows: Ln TFP = ln Y – (ln K + ln L), Where TFP is total factor productivity Y is GDP at constant prices K is capital stock L is labor force The first step we regressed business entry (as the dependent variable) on cost of starting business (% of GNI / Capita), time to start business, trade (% of GDP), and number of trademarks registered which are some variables correlated with innovative entrepreneur as discussed in the above literature. Second we predict a variable called entrepreneurship based on the coefficient of the previous regression. Third we use this newly estimated variable as a regressor where total factor productivity is the dependent variable. Other set of explanatory variables are added as research and development exp. (% of GDP), Tertiary school enrollment, imports (% of GDP), exports (% of GDP), and inflation (measured by the deflator). TFP = α 0 + α1ENT + α2 rd_exp + α3 sch_terr + α4 imports + α5 exports + α6 inflat 3.3 Regression results The first run of regressions is presented in Table 3; where we regressed business entry rate on cost of starting business, time to start business, trade as % of GDP and number of trade marks. Than we predict entrepreneurship coefficient which turns out to be positive and statistically significant. Second we use this newly estimated variable as a regressor, entrepreneur coefficient, where factor productivity total is the dependent variable. Other set of explanatory variables are added as research and development exp. (% of GDP), tertiary school enrollment, imports (% of GDP), exports (% of GDP), and inflation (measured by the deflator). These results showed that total factor productivity is significant and positively correlated with entrepreneurship; albeit somewhat lower when OLS estimation techniques are used, suggesting that there is a positive relationship between research and development, tertiary school


enrolment, imports and inflation. Moreover, it is negatively correlated with imports. Results are presented in table 4. Thus, entrepreneurship is one instrument that may add to the effect of knowledge investments through R&D. This is certainly consistent with the recent statistical, systematic empirical evidence linking measures of entrepreneurship to economic growth. Implementing different regression techniques we find surprisingly robust support for entrepreneurship being one important source of growth. Due to the limitation of the data; as we planned to estimate for each group of the human development index, group one only provide positively significant relation between total factor productivity and entrepreneurship, other explanatory variable, see table 5 and 5.1. We suggest that the reason behind the insignificance is related to the stage of the economic setting of the other groups as they are lag behind and cannot catch the start up stage. As they include countries in different stages of the economic development. We planned to estimate for the marginal effect of entrepreneurship and other economic variables on TFP in Egypt but data limitation hinder us to achieve our objective. 4. Conclusion Improving our perceptive of the importance role played by entrepreneurship in the developing countries is corner stone to adopt the suitable public policy planning. Implication showed a positive impact of entrepreneurs on total factor productivity. Another significant finding is that the role of entrepreneurs in spurring TFP is necessary but not sufficient; a sufficient condition would be stable economic settings “rules of the game” to maximize the effect of entrepreneurship on TFP.

This significant and forceful contribution of the endogenous growth theory was to refocus the policy debate away from the stress on enhancing capital and labor only to a new priority on knowledge and human capital. This paper stresses on the importance of entrepreneurship that affect productivity and promote growth. As this paper suggests, while generating knowledge and human capital may be a necessary condition for economic growth, it is not sufficient. Rather, a supplementary set institutional settings that promote growth.


Appendix I: List and definition of variables

Table 1 Statistical results

Table 1.A

Statistical results

Table 2. List and definition of variables Variables Names Total factor productivity tfp Cost of starting business cost_buss_gnic Time to start business time_strt Trade (% of gdp), trade_gdp Number of trademarks registered trdmrk_tot Entrepreneurship entrep Research and development exp. (% of gdp) rd_exp Tertiary school enrollment sch_terr_gross Imports (% of gdp) imports_gdp Exports (% of gdp) exports_gdp Inflation. inflation_def

entryrate .4580665 .0498557 9.19 0.000 .3584978 .5576353 growthrate Coef. Std. Err. t P>|t| [95% Conf. Interval]

Total .237799993 66 .00360303 Root MSE = .03989 Adj R-squared = 0.5583 Residual .103449082 65 .001591524 R-squared = 0.5650 Model .134350911 1 .134350911 Prob > F = 0.0000 F( 1, 65) = 84.42 Source SS df MS Number of obs = 66

. regress growthrate entryrate, noconstant

.

_cons 16.22998 1.406782 11.54 0.000 13.3845 19.07547gdppercapi~2 3.89e-09 1.35e-09 2.89 0.006 1.16e-09 6.61e-09gdppercap~08 -.0004144 .000101 -4.10 0.000 -.0006186 -.0002101 totalentre~x Coef. Std. Err. t P>|t| [95% Conf. Interval]

Total 1614.30998 41 39.3734141 Root MSE = 5.0378 Adj R-squared = 0.3554 Residual 989.788761 39 25.379199 R-squared = 0.3869 Model 624.521217 2 312.260609 Prob > F = 0.0001 F( 2, 39) = 12.30 Source SS df MS Number of obs = 42


Table 3

Regress business entry on cost of starting business (% of GNI / Capita) , time to start business , trade (% of GDP), and number of trademarks registered

(1) VARIABLES buss_ent cost_buss_gniC -0.0257*** (0.00860) time_strt -0.0365*** (0.00818) trade_gdp 0.0132*** (0.00312) trdmrk_tot 1.06e-05* (5.95e-06) Constant 9.572*** (0.535) Observations 255 R-squared 0.254

Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

Table – 4 Sample statistics

Regress tfp (total factor productivity) on entrep; research and development exp. (% of GDP), Tertiary school enrollment, imports (% of GDP), exports (% of GDP), and inflation.

(1) VARIABLES tfp entrep 0.0280*** (0.00685) rd_exp 0.180*** (0.0363) sch_terr_gross 0.00939*** (0.00110) imports_gdp -0.00410*** (0.000755) exports_gdp 0.00190* (0.000999) inflation_def 0.00335*** (0.00117) Constant 5.067*** (0.0899) Observations 277 Number of country 74



If we repeat step 3 without inflation

(1) VARIABLES tfp1 entrep 0.0309*** (0.00666) rd_exp 0.148*** (0.0358) sch_terr_gross 0.00882*** (0.00108) imports_gdp -0.00370*** (0.000733) exports_gdp 0.00211** (0.000972) Constant 5.092*** (0.0931) Observations 277 Number of country 74



Table 5- Group one Statistical results

(1) VARIABLES buss_ent cost_bus_start -0.131** (0.0586) time_start -0.0539*** (0.0184) trade 0.0106*** (0.00336) Constant 11.33*** (0.652) Observations 115 R-squared 0.294


Table 5.1- Group one Statistical results

(1) VARIABLES tfp1 rd_exp 0.0440*** (0.0157) scl_ter 0.00117*** (0.000379) exports_gdp 0.00254*** (0.000878) imports_gdp 6.41e-05 (0.000959) inflation_def 0.00218** (0.000973) Constant 6.615*** (0.0635) Observations 193 Number of country 29



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